Unsupervised Learning of Sparse Facial Movements using Convolutional Spiking Neural Networks

This contribution explores the use of a single task-dependant 3D convolutional spiking neural layer for recognizing subtle facial expressions. Using biologically inspired mechanisms like STDP, latency coding and task specific knowledge, we show that even with a shallow architecture, one can improve the learning of meaningful spatio-temporal features.